Abstract: Macromolecular Imaging of Gray and White Matter Pathology in Multiple Sclerosis Multiple sclerosis (MS) is a complex inflammatory, demyelinating, neurodegenerative disease of the central nervous system, highly variable in its symptoms, clinical course, and underlying pathological changes in the brain. Conventional magnetic resonance imaging (cMRI) is essential to diagnosis and management of MS but it lacks sufficient sensitivity and specificity to MS pathology, correlates poorly with clinical disability and has limited prognostic value. In particular, cMRI fails to detect most of the disease burden in cortical gray matter (GM), recently recognized as a major site of pathology in MS, which is now understood to be a whole-brain (not exclusively white matter) disease. More sensitive, specific, and reliable imaging biomarkers are critically needed for earlier diagnosis and more accurate monitoring of disease progression and therapy. The overarching aim of this proposal is to meet this need through development of novel, clinically feasible, quantitative MRI methods based on the phenomenon of magnetization transfer (MT), a powerful yet underdeveloped method to quantify macromolecular changes in tissue. Despite a large volume of published work to date, MT imaging in its present form still lacks sufficient sensitivity, specificity, and reliability to meet the needs of MS management and clinical research. So-called quantitative MT imaging (qMTI) was developed to correct these deficiencies. The principal qMTI parameter, macromolecular pool fraction, has been shown to reflect myelin content and, when measured in cortical GM, predict clinical disability more accurately than any other imaging measure studied. These results could herald a paradigm shift in the assessment of MS as whole-brain disease; however, several obstacles still impede the application of qMTI in clinical and clinical research settings. The first aim of this proposal will be to develop the next-generation qMTI methodology immune to cerebrospinal fluid partial volume effects and corrected for factors affecting tissue water content (edema/inflammation/gliosis), all optimized for imaging with a minimum number of MRI acquisitions. The second aim will be to accelerate the constituent image acquisitions for this protocol, yielding a fast, robust, high- resolution implementation of qMTI for clinical settings. Finally, the third aim will be to validate the clinical utility of the new qMTI biomarkers in a cross-sectional cohort of MS patients and age-matched controls. Specifically, we will determine whether they predict cognitive impairment more accurately than existing imaging methods.